Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling

Evaluation Research on Military Logistics Distribution Center Based on SVM

Authors
Yang Fan, Zhao Zhanbiao, Jiang Tianyuan, Dong Yucai
Corresponding Author
Yang Fan
Available Online June 2015.
DOI
10.2991/kam-15.2015.57How to use a DOI?
Keywords
support vector machines (SVM); military logistics; distribution center.
Abstract

It is of vital importance to evaluate scientifically and accurately the ability of military logistics distribution center for promoting distribution efficiency and satisfying war requirements. Faced with the problem of low accuracy in evaluating the ability of current military logistics distribution center, this paper established an evaluation model with support vector regression, in which it shows great fitting efficiency with average relative error of 1.7536% after training the samples. Support vector machine promotes generalization ability through structural risk minimization, thus solving such practical problems as small sample data, non-lineal, high dimensions and local minima, which plays a significant role in evaluating the ability of military logistics distribution center.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
10.2991/kam-15.2015.57
ISSN
1951-6851
DOI
10.2991/kam-15.2015.57How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yang Fan
AU  - Zhao Zhanbiao
AU  - Jiang Tianyuan
AU  - Dong Yucai
PY  - 2015/06
DA  - 2015/06
TI  - Evaluation Research on Military Logistics Distribution Center Based on SVM
BT  - Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
PB  - Atlantis Press
SP  - 210
EP  - 212
SN  - 1951-6851
UR  - https://doi.org/10.2991/kam-15.2015.57
DO  - 10.2991/kam-15.2015.57
ID  - Fan2015/06
ER  -